Respond-CAM: Analyzing Deep Models for 3D Imaging Data by Visualizations

Respond-CAM: Analyzing Deep Models for 3D Imaging Data by Visualizations

31 May 2018

Papers citing "Respond-CAM: Analyzing Deep Models for 3D Imaging Data by Visualizations"

19 / 19 papers shown

Title
LCE: A Framework for Explainability of DNNs for Ultrasound Image Based on Concept Discovery Weiji Kong Xun Gong Juan Wang 26 1 0 19 Aug 2024
SE3D: A Framework For Saliency Method Evaluation In 3D Imaging Mariusz Wi'sniewski Loris Giulivi Giacomo Boracchi 37 1 0 23 May 2024
DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications Adam Ivankay Mattia Rigotti P. Frossard OOD MedIm 39 1 0 05 Jul 2023
Explainable AI for Bioinformatics: Methods, Tools, and Applications Md. Rezaul Karim Tanhim Islam Oya Beyan Christoph Lange Michael Cochez Dietrich-Rebholz Schuhmann Stefan Decker 34 68 0 25 Dec 2022
Explainable Medical Imaging AI Needs Human-Centered Design: Guidelines and Evidence from a Systematic Review Haomin Chen Catalina Gomez Chien-Ming Huang Mathias Unberath 27 121 0 21 Dec 2021
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods Zohaib Salahuddin Henry C. Woodruff A. Chatterjee Philippe Lambin 29 306 0 01 Nov 2021
BI-RADS-Net: An Explainable Multitask Learning Approach for Cancer Diagnosis in Breast Ultrasound Images Boyu Zhang Aleksandar Vakanski Min Xian 30 11 0 05 Oct 2021
Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data Sebastian Polsterl Christina Aigner Christian Wachinger FAtt 27 4 0 13 Jul 2021
Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond Xuhong Li Haoyi Xiong Xingjian Li Xuanyu Wu Xiao Zhang Ji Liu Jiang Bian Dejing Dou AAML FaML XAI HAI 23 318 0 19 Mar 2021
Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyond Guang Yang Qinghao Ye Jun Xia 92 484 0 03 Feb 2021
Quantifying Explainability of Saliency Methods in Deep Neural Networks with a Synthetic Dataset Erico Tjoa Cuntai Guan XAI FAtt 19 27 0 07 Sep 2020
An Adversarial Approach for Explaining the Predictions of Deep Neural Networks Arash Rahnama A.-Yu Tseng FAtt AAML FaML 25 5 0 20 May 2020
HR-CAM: Precise Localization of Pathology Using Multi-level Learning in CNNs Sumeet Shinde Tanay Chougule Jitender Saini M. Ingalhalikar 13 13 0 23 Sep 2019
CT Data Curation for Liver Patients: Phase Recognition in Dynamic Contrast-Enhanced CT Bo Zhou Adam P. Harrison Jiawen Yao Chi-Tung Cheng Jing Xiao Chien-Hung Liao Le Lu 23 11 0 05 Sep 2019
Deep Learning-Based Strategy for Macromolecules Classification with Imbalanced Data from Cellular Electron Cryotomography Ziqian Luo Xiangrui Zeng Zhipeng Bao Min Xu 16 46 0 27 Aug 2019
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI Erico Tjoa Cuntai Guan XAI 56 1,417 0 17 Jul 2019
Going Deep in Medical Image Analysis: Concepts, Methods, Challenges and Future Directions F. Altaf Syed Mohammed Shamsul Islam Naveed Akhtar N. Janjua OOD 34 200 0 15 Feb 2019
Feature Decomposition Based Saliency Detection in Electron Cryo-Tomograms Bo Zhou Qiang Guo Xiangrui Zeng Min Xu 19 8 0 31 Jan 2018
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 355 10,639 0 19 Feb 2017